AI Engineer | Data Scientist | Building GenAI & Agentic Workflows at Scale
From raw data chaos to enterprise automation, I architect, ship, and scale real-world AI solutions.
- Key Strengths:
- GenAI & LLMs: Ollama, OpenAI, Azure OpenAI, WatsonX, LangChain, LangGraph, Llama, Gemma, RAG, LLMOps
- ML Engineering: Python, scikit-learn, XGBoost, TensorFlow, PySpark, Databricks, advanced feature engineering, model explainability
- DevOps & MLOps: GitHub Actions, Jenkins, Docker, CI/CD, IBM Watson Studio, OpenScale, monitoring, audit pipelines
- Data Engineering: Pandas, NumPy, Spark, MongoDB, MySQL, BigQuery, Power BI, data pipeline automation
- Visualization: Power BI, Tableau, DAX, Python (Matplotlib, Seaborn, Plotly)
- Core Math/Stats: Probability, Bayesian, Hypothesis Testing, A/B, t-Test, ANOVA, Chi-Square, clustering, segmentation
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🌱 Currently learning: Deep dives into advanced GenAI architectures, retrieval-augmented generation (RAG), and agentic LLM workflows.
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💬 Ask me about: Real-world LLM deployment, GenAI for document automation, scalable ML pipelines, explainable AI, advanced MLOps, or simply Python/data science best practices.
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📫 Contact: sunnypanchalin@gmail.com
Always building. Always learning. Always keeping it real.
Drop me a note if you want to chat GenAI, MLE, or real-world AI engineering!